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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Occupational and patient exposure as well as image quality for full spine examinations with the EOS imaging system

Purpose: EOS (EOS imaging S.A, Paris, France) is an x-ray imaging system that uses slot-scanning technology in order to optimize the trade-off between image quality and dose. The goal of this study was to characterize the EOS system in terms of occupational exposure, organ doses to patients as well as image quality for full spine examinations. Methods: Occupational exposure was determined by measuring the ambient dose equivalents in the radiological room during a standard full spine examination. The patient dosimetry was performed using anthropomorphic phantoms representing an adolescent and a five-year-old child. The organ doses were measured with thermoluminescent detectors and then used to calculate effective doses. Patient exposure with EOS was then compared to dose levels reported for conventional radiological systems. Image quality was assessed in terms of spatial resolution and different noise contributions to evaluate the detector's performances of the system. The spatial-frequency signal transfer efficiency of the imaging system was quantified by the detective quantum efficiency (DQE). Results: The use of a protective apron when the medical staff or parents have to stand near to the cubicle in the radiological room is recommended. The estimated effective dose to patients undergoing a full spine examination with the EOS system was 290μSv for an adult and 200 μSv for a child. MTF and NPS are nonisotropic, with higher values in the scanning direction; they are in addition energy-dependent, but scanning speed independent. The system was shown to be quantum-limited, with a maximum DQE of 13%. The relevance of the DQE for slot-scanning system has been addressed. Conclusions: As a summary, the estimated effective dose was 290μSv for an adult; the image quality remains comparable to conventional systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-I-62: Assessing Radiation Dose Reduction and CT Image Optimization Through the Measurement and Analysis of the Detector Quantum Efficiency (DQE) of CT Images Using Different Beam Hardening Filters

Purpose: Reducing patient dose while maintaining (or even improving) image quality is one of the foremost goals in CT imaging. To this end, we consider the feasibility of optimizing CT scan protocols in conjunction with the application of different beam-hardening filtrations and assess this augmentation through noise-power spectrum (NPS) and detector quantum efficiency (DQE) analysis. Methods: American College of Radiology (ACR) and Catphan phantoms (The Phantom Laboratory) were scanned with a 64 slice CT scanner when additional filtration of thickness and composition (e.g., copper, nickel, tantalum, titanium, and tungsten) had been applied. A MATLAB-based code was employed to calculate the image of noise NPS. The Catphan Image Owl software suite was then used to compute the modulated transfer function (MTF) responses of the scanner. The DQE for each additional filter, including the inherent filtration, was then computed from these values. Finally, CT dose index (CTDIvol) values were obtained for each applied filtration through the use of a 100 mm pencil ionization chamber and CT dose phantom. Results: NPS, MTF, and DQE values were computed for each applied filtration and compared to the reference case of inherent beam-hardening filtration only. Results showed that the NPS values were reduced between 5 and 12% compared to inherent filtration case. Additionally, CTDIvol values were reduced between 15 and 27% depending on the composition of filtration applied. However, no noticeable changes in image contrast-to-noise ratios were noted. Conclusion: The reduction in the quanta noise section of the NPS profile found in this phantom-based study is encouraging. The reduction in both noise and dose through the application of beam-hardening filters is reflected in our phantom image quality. However, further investigation is needed to ascertain the applicability of this approach to reducing patient dose while maintaining diagnostically acceptable image qualities in a clinical setting.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-J-47: Comparison of Online Image Registrations of Varian TrueBeam Cone-Beam CT and BrainLab ExacTrac Imaging Systems

Purpose To compare online image registrations of TrueBeam cone-beam CT (CBCT) and BrainLab ExacTrac imaging systems. Methods Tests were performed on a Varian TrueBeam STx linear accelerator (Version 2.0), which is integrated with a BrainLab ExacTrac imaging system (Version 6.0.5). The study was focused on comparing the online image registrations for translational shifts. A Rando head phantom was placed on treatment couch and immobilized with a BrainLab mask. The phantom was shifted by moving the couch translationally for 8 mm with a step size of 1 mm, in vertical, longitudinal, and lateral directions, respectively. At each location, the phantom was imaged with CBCT and ExacTrac x-ray. CBCT images were registered with TrueBeam and ExacTrac online registration algorithms, respectively. And ExacTrac x-ray image registrations were performed. Shifts calculated from different registrations were compared with nominal couch shifts. Results The averages and ranges of absolute differences between couch shifts and calculated phantom shifts obtained from ExacTrac x-ray registration, ExacTrac CBCT registration with default window, ExaxTrac CBCT registration with adjusted window (bone), Truebeam CBCT registration with bone window, and Truebeam CBCT registration with soft tissue window, were: 0.07 (0.02–0.14), 0.14 (0.01–0.35), 0.12 (0.02–0.28), 0.09 (0–0.20), and 0.06 (0–0.10) mm, in vertical direction; 0.06 (0.01–0.12), 0.27 (0.07–0.57), 0.23 (0.02–0.48), 0.04 (0–0.10), and 0.08 (0– 0.20) mm, in longitudinal direction; 0.05 (0.01–0.21), 0.35 (0.14–0.80), 0.25 (0.01–0.56), 0.19 (0–0.40), and 0.20 (0–0.40) mm, in lateral direction. Conclusion The shifts calculated from ExacTrac x-ray and TrueBeam CBCT registrations were close to each other (the differences between were less than 0.40 mm in any direction), and had better agreements with couch shifts than those from ExacTrac CBCT registrations. There were no significant differences between TrueBeam CBCT registrations using different windows. In ExacTrac CBCT registrations, using bone window led to better agreements than using default window.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-G-BRA-08: BEST IN PHYSICS (JOINT IMAGING-THERAPY): Hybrid PET-MRI Imaging of Acute Radiation Induced Cardiac Toxicity

Purpose: To identify the presence of low-dose radiation induced cardiac toxicity in a canine model using hybrid positron emission tomography (PET) and magnetic resonance imaging (MRI). Methods: Research ethics board approval was obtained for a longitudinal imaging study of 5 canines after cardiac irradiation. Animals were imaged at baseline, 1 week post cardiac irradiation, and 1 month post cardiac irradiation using a hybrid PET- MRI system (Biograph mMR, Siemens Healthcare). The imaging protocol was designed to assess acute changes in myocardial perfusion and inflammation. Myocardial perfusion imaging was performed using N13-ammonia tracer followed by a dynamic PET acquisition scan. A compartmental tracer kinetic model was used for absolute perfusion quantification. Myocardial inflammation imaging was performed using F18-fluorodeoxyglucose (FDG) tracer. The standard uptake value (SUV) over a region encompassing the whole heart was used to compare FDG scans. All animals received a simulation CT scan (GE Medical Systems) for radiation treatment planning. Radiation treatment plans were created using the Pinncale3 treatment planning system (Philips Radiation Oncology Systems) and designed to resemble the typical cardiac exposure during left-sided breast cancer radiotherapy. Cardiac irradiations were performed in a single fraction using a TrueBeam linear accelerator (Varian Medical Systems). Results: The delivered dose (mean ± standard deviation) to heart was 1.8±0.2 Gy. Reductions in myocardial stress perfusion relative to baseline were observed in 2 of the 5 animals 1 month post radiation. A global inflammatory response 1 month post radiation was observed in 4 of the 5 animals. The calculated SUV at 1 month post radiation was significantly higher (p=0.05) than the baseline SUV. Conclusion: Low doses of cardiac irradiation (< 2 Gy) may lead to myocardial perfusion defects and a global inflammatory response that can be detectable as early as 1 month post irradiation using hybrid PET-MRI imaging techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Quantitative correlational study of microbubble-enhanced ultrasound imaging and magnetic resonance imaging of glioma and early response to radiotherapy in a rat model

Purpose: Radiotherapy remains a major treatment method for malignant tumors. Magnetic resonance imaging (MRI) is the standard modality for assessing glioma treatment response in the clinic. Compared to MRI, ultrasound imaging is low-cost and portable and can be used during intraoperative procedures. The purpose of this study was to quantitatively compare contrast-enhanced ultrasound (CEUS) imaging and MRI of irradiated gliomas in rats and to determine which quantitative ultrasound imaging parameters can be used for the assessment of early response to radiation in glioma. Methods: Thirteen nude rats with U87 glioma were used. A small thinned skull window preparation was performed to facilitate ultrasound imaging and mimic intraoperative procedures. Both CEUS and MRI with structural, functional, and molecular imaging parameters were performed at preradiation and at 1 day and 4 days postradiation. Statistical analysis was performed to determine the correlations between MRI and CEUS parameters and the changes between pre- and postradiation imaging. Results: Area under the curve (AUC) in CEUS showed significant difference between preradiation and 4 days postradiation, along with four MRI parameters, T{sub 2}, apparent diffusion coefficient, cerebral blood flow, and amide proton transfer-weighted (APTw) (all p < 0.05). The APTw signal was correlated with three CEUS parameters, rise time (r = − 0.527, p < 0.05), time to peak (r = − 0.501, p < 0.05), and perfusion index (r = 458, p < 0.05). Cerebral blood flow was correlated with rise time (r = − 0.589, p < 0.01) and time to peak (r = − 0.543, p < 0.05). Conclusions: MRI can be used for the assessment of radiotherapy treatment response and CEUS with AUC as a new technique and can also be one of the assessment methods for early response to radiation in glioma.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

An investigation of kV CBCT image quality and dose reduction for volume-of-interest imaging using dynamic collimation

Purpose: The focus of this work was to investigate the improvements in image quality and dose reduction for volume-of-interest (VOI) kilovoltage-cone beam CT (CBCT) using dynamic collimation. Methods: A prototype iris aperture was used to track a VOI during a CBCT acquisition. The current aperture design is capable of 1D translation as a function of gantry angle and dynamic adjustment of the iris radius. The aperture occupies the location of the bow-tie filter on a Varian On-Board Imager system. CBCT and planar image quality were investigated as a function of aperture radius, while maintaining the same dose to the VOI, for a 20 cm diameter cylindrical water phantom with a 9 mm diameter bone insert centered on isocenter. Corresponding scatter-to-primary ratios (SPR) were determined at the detector plane with Monte Carlo simulation using EGSnrc. Dose distributions for various sizes VOI were modeled using a dynamic BEAMnrc library and DOSXYZnrc. The resulting VOI dose distributions were compared to full-field distributions. Results: SPR was reduced by a factor of 8.4 when decreasing iris diameter from 21.2 to 2.4 cm (at isocenter). Depending upon VOI location and size, dose was reduced to 16%–90% of the full-field value along the central axis plane and down to 4% along the axis of rotation, while maintaining the same dose to the VOI compared to full-field techniques. When maintaining constant dose to the VOI, this change in iris diameter corresponds to a factor increase of approximately 1.6 in image contrast and a factor decrease in image noise of approximately 1.2. This results in a measured gain in contrast-to-noise ratio by a factor of approximately 2.0. Conclusions: The presented VOI technique offers improved image quality for image-guided radiotherapy while sparing the surrounding volume of unnecessary dose compared to full-field techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-BRA-04: Computerized Framework for Marker-Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image-Guided Radiation Therapy

Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed framework might be useful for tasks involving feature-based image registration in range-image guided radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-05: Multidimensional Imaging Radiomics-Geodesics: A Novel Manifold Learning Based Automatic Feature Extraction Method for Diagnostic Prediction in Multiparametric Imaging

Purpose: Multiparametric radiological imaging is used for diagnosis in patients. Potentially extracting useful features specific to a patient’s pathology would be crucial step towards personalized medicine and assessing treatment options. In order to automatically extract features directly from multiparametric radiological imaging datasets, we developed an advanced unsupervised machine learning algorithm called the multidimensional imaging radiomics-geodesics(MIRaGe). Methods: Seventy-six breast tumor patients underwent 3T MRI breast imaging were used for this study. We tested the MIRaGe algorithm to extract features for classification of breast tumors into benign or malignant. The MRI parameters used were T1-weighted, T2-weighted, dynamic contrast enhanced MR imaging (DCE-MRI) and diffusion weighted imaging(DWI). The MIRaGe algorithm extracted the radiomics-geodesics features (RGFs) from multiparametric MRI datasets. This enable our method to learn the intrinsic manifold representations corresponding to the patients. To determine the informative RGF, a modified Isomap algorithm(t-Isomap) was created for a radiomics-geodesics feature space(tRGFS) to avoid overfitting. Final classification was performed using SVM. The predictive power of the RGFs was tested and validated using k-fold cross validation. Results: The RGFs extracted by the MIRaGe algorithm successfully classified malignant lesions from benign lesions with a sensitivity of 93% and a specificity of 91%. The top 50 RGFs identified as the most predictive by the t-Isomap procedure were consistent with the radiological parameters known to be associated with breast cancer diagnosis and were categorized as kinetic curve characterizing RGFs, wash-in rate characterizing RGFs, wash-out rate characterizing RGFs and morphology characterizing RGFs. Conclusion: In this paper, we developed a novel feature extraction algorithm for multiparametric radiological imaging. The results demonstrated the power of the MIRaGe algorithm at automatically discovering useful feature representations directly from the raw multiparametric MRI data. In conclusion, the MIRaGe informatics model provides a powerful tool with applicability in cancer diagnosis and a possibility of extension to other kinds of pathologies. NIH (P50CA103175, 5P30CA006973 (IRAT), R01CA190299, U01CA140204), Siemens Medical Systems (JHU-2012-MR-86-01) and Nivida Graphics Corporation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-AB-BRA-07: Low Dose Imaging with Avalanche Amorphous Selenium Flat Panel Imager

Purpose: We present the first active matrix flat panel imager (AMFPI) capable of producing x-ray quantum noise limited images at low doses by overcoming the electronic noise through signal amplification by photoconductive avalanche gain (gav). The indirect detector fabricated uses an optical sensing layer of amorphous selenium (a-Se) known as High-Gain Avalanche Rushing Photoconductor (HARP). The detector design is called Scintillator HARP (SHARP)-AMFPI. This is the first image sensor to utilize solid-state HARP technology. Methods: The detector’s electronic readout is a 24 × 30 cm{sup 2} array of thin film transistors (TFT) with a pixel pitch of 85 µm. The HARP structure consists of a 15 µm layer of a-Se isolated from the high voltage (HV) and signal electrode by a 2 µm thick hole blocking layer and electron blocking layer, respectively, to reduce dark current. A 150 µm thick structured CsI scintillator with reflective backing and a fiber optic faceplate (FOP) was coupled to the semi-transparent HV bias electrode of the HARP structure. Images were acquired using a 30 kVp Mo/Mo spectrum typically used in mammography. Results: Optical sensitivity measurements demonstrate that gav = 76 ± 5 can be achieved over the entire active area of the detector. At a constant dose to the detector of 6.67 µGy, image quality increases with gav until the effective electronic noise is negligible. Quantum noise limited images can be obtained with doses as low as 0.18 µGy. Conclusion: We demonstrate the feasibility of utilizing avalanche gain to overcome electronic noise. The indirect detector fabricated is the first solid-state imaging sensor to use HARP, and the largest active area HARP sensor to date. Our future work is to improve charge transport within the HARP structure and utilize a transparent HV electrode.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-207A-02: A Feature-Preserving Image Reconstruction Method for Improved Pancreaticlesion Classification in Diagnostic CT Imaging

Purpose: To develop a feature-preserving model based image reconstruction (MBIR) method that improves performance in pancreatic lesion classification at equal or reduced radiation dose. Methods: A set of pancreatic lesion models was created with both benign and premalignant lesion types. These two classes of lesions are distinguished by their fine internal structures; their delineation is therefore crucial to the task of pancreatic lesion classification. To reduce image noise while preserving the features of the lesions, we developed a MBIR method with curvature-based regularization. The novel regularization encourages formation of smooth surfaces that model both the exterior shape and the internal features of pancreatic lesions. Given that the curvature depends on the unknown image, image reconstruction or denoising becomes a non-convex optimization problem; to address this issue an iterative-reweighting scheme was used to calculate and update the curvature using the image from the previous iteration. Evaluation was carried out with insertion of the lesion models into the pancreas of a patient CT image. Results: Visual inspection was used to compare conventional TV regularization with our curvature-based regularization. Several penalty-strengths were considered for TV regularization, all of which resulted in erasing portions of the septation (thin partition) in a premalignant lesion. At matched noise variance (50% noise reduction in the patient stomach region), the connectivity of the septation was well preserved using the proposed curvature-based method. Conclusion: The curvature-based regularization is able to reduce image noise while simultaneously preserving the lesion features. This method could potentially improve task performance for pancreatic lesion classification at equal or reduced radiation dose. The result is of high significance for longitudinal surveillance studies of patients with pancreatic cysts, which may develop into pancreatic cancer. The Senior Author receives financial support from Siemens GmbH Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A Heuristic Approach to Remove the Background Intensity on White-light Solar Images. I. STEREO /HI-1 Heliospheric Images

White-light coronal and heliospheric imagers observe scattering of photospheric light from both dust particles (the F-Corona) and free electrons in the corona (the K-corona). The separation of the two coronae is thus vitally important to reveal the faint K-coronal structures (e.g., streamers, co-rotating interaction regions, coronal mass ejections, etc.). However, the separation of the two coronae is very difficult, so we are content in defining a background corona that contains the F- and as little K- as possible. For both the LASCO-C2 and LASCO-C3 coronagraphs aboard the Solar and Heliospheric Observatory ( SOHO ) and the white-light imagers of the SECCHI suite aboard the Solar Terrestrial Relationships Observatory ( STEREO ), a time-dependent model of the background corona is generated from about a month of similar images. The creation of such models is possible because the missions carrying these instruments are orbiting the Sun at about 1 au. However, the orbit profiles for the upcoming Solar Orbiter and Solar Probe Plus missions are very different. These missions will have elliptic orbits with a rapidly changing radial distance, hence invalidating the techniques in use for the SOHO /LASCO and STEREO /SECCHI instruments. We have been investigating techniques to generate background models out of just single images that could be used for the Solar Orbiter Heliospheric Imager and the Wide-field Imager for the Solar Probe Plus packages on board the respective spacecraft. In this paper, we introduce a state-of-the-art, heuristic technique to create the background intensity models of STEREO /HI-1 data based solely on individual images, report on new results derived from its application, and discuss its relevance to instrumental and operational issues.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Development of Simultaneous Beta-and-Coincidence-Gamma Imager for Plant Imaging Research

The goal of this project is to develop a novel imaging system that can simultaneously acquire beta and coincidence gamma images of positron sources in thin objects such as leaves of plants. This hybrid imager can be used to measure carbon assimilation in plants quantitatively and in real-time after C-11 labeled carbon-dioxide is administered. A better understanding of carbon assimilation, particularly under the increasingly elevated atmospheric CO 2 level, is extremely critical for plant scientists who study food crop and biofuel production. Phase 1 of this project is focused on the technology development with 3 specific aims: (1) develop a hybrid detector that can detect beta and gamma rays simultaneously; (2) develop an imaging system that can differentiate these two types of radiation and acquire beta and coincidence gamma images in real-time; (3) develop techniques to quantify radiotracer distribution using beta and gamma images. Phase 2 of this project is to apply technologies developed in phase 1 to study plants using positron-emitting radionuclide such as 11 C to study carbon assimilation in biofuel plants.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Full-Depth Coadds of the WISE and First-Year NEOWISE-Reactivation Images

The Near Earth Object Wide-field Infrared Survey Explorer (NEOWISE) Reactivation mission released data from its first full year of observations in 2015. This data set includes ~2.5 million exposures in each of W1 and W2, effectively doubling the amount of WISE imaging available at 3.4 μm and 4.6 μm relative to the AllWISE release. In this paper, we have created the first ever full-sky set of coadds combining all publicly available W1 and W2 exposures from both the AllWISE and NEOWISE-Reactivation (NEOWISER) mission phases. We employ an adaptation of the unWISE image coaddition framework, which preserves the native WISE angular resolution and is optimized for forced photometry. By incorporating two additional scans of the entire sky, we not only improve the W1/W2 depths, but also largely eliminate time-dependent artifacts such as off-axis scattered moonlight. We anticipate that our new coadds will have a broad range of applications, including target selection for upcoming spectroscopic cosmology surveys, identification of distant/massive galaxy clusters, and discovery of high-redshift quasars. In particular, our full-depth AllWISE+NEOWISER coadds will be an important input for the Dark Energy Spectroscopic Instrument selection of luminous red galaxy and quasar targets. Our full-depth W1/W2 coadds are already in use within the DECam Legacy Survey (DECaLS) and Mayall z-band Legacy Survey (MzLS) reduction pipelines. Finally, much more work still remains in order to fully leverage NEOWISER imaging for astrophysical applications beyond the solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to farming, forest management and climate change. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and our own code was used to noninvasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure at 31µm resolution, and extract quantitative information (root volume and surface area) from the 3D data, respectively. Based on the mesh generated from the root structure, computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. The flow variability and soil water distributions under different scenarios were investigated. Parameterizations were evaluated to show their impacts on the average conductivity. The pore-scale modeling approach provides realistic simulations of rhizosphere flow processes and provides useful information that can be linked to upscaled models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Imaging Taurine in the Central Nervous System Using Chemically Specific X-ray Fluorescence Imaging at the Sulfur K-Edge

A method to image taurine distributions within the central nervous system and other organs has long been sought. Since taurine is small and mobile, it cannot be chemically “tagged” and imaged using conventional immuno-histochemistry methods. Combining numerous indirect measurements, taurine is known to play critical roles in brain function during health and disease and is proposed to act as a neuro-osmolyte, neuro-modulator, and possibly a neuro-transmitter. Elucidation of taurine’s neurochemical roles and importance would be substantially enhanced by a direct method to visualize alterations, due to physiological and pathological events in the brain, in the local concentration of taurine at or near cellular spatial resolution in vivo or in situ in tissue sections. We thus have developed chemically specific X-ray fluorescence imaging (XFI) at the sulfur K-edge to image the sulfonate group in taurine in situ in ex vivo tissue sections. To our knowledge, this represents the first undistorted imaging of taurine distribution in brain at 20 μm resolution. We report quantitative technique validation by imaging taurine in the cerebellum and hippocampus regions of the rat brain. Further, we apply the technique to image taurine loss from the vulnerable CA1 (cornus ammonis 1) sector of the rat hippocampus following global brain ischemia. Furthermore, the location-specific loss of taurine from CA1 but not CA3 neurons following ischemia reveals osmotic stress may be a key factor in delayed neurodegeneration after a cerebral ischemic insult and highlights the significant potential of chemically specific XFI to study the role of taurine in brain disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-I-82: Improving CT Image Quality for Radiation Therapy Using Iterative Reconstruction Algorithms and Slightly Increasing Imaging Doses

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. For CT in radiation therapy (RT), slightly increasing imaging dose to improve IQ may be justified if it can substantially enhance structure delineation. The purpose of this study is to investigate and to quantify the IQ enhancement as a result of increasing imaging doses and using IR algorithms. Methods: CT images were acquired for phantoms, built to evaluate IQ metrics including spatial resolution, contrast and noise, with a variety of imaging protocols using a CT scanner (Definition AS Open, Siemens) installed inside a Linac room. Representative patients were scanned once the protocols were optimized. Both phantom and patient scans were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and the Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared. Results: IR techniques are demonstrated to preserve spatial resolution as measured by the point spread function and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is doubled by adopting the highest SAFIRE strength. As expected, increasing imaging dose reduces noise for both SAFIRE and FBP reconstructions. The contrast to noise increases from 3 to 5 by increasing the dose by a factor of 4. Similar IQ improvement was observed on the CTs for selected patients with pancreas and prostrate cancers. Conclusion: The IR techniques produce a measurable enhancement to CT IQ by reducing the noise. Increasing imaging dose further reduces noise independent of the IR techniques. The improved CT enables more accurate delineation of tumors and/or organs at risk during RT planning and delivery guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗